Outdoor control of UAVs is normally accomplished using GPS. Usually, the operator has a map of the area where he/she is interested in sending the UAV. By selecting a series of waypoints on the map, it delineates the trajectory followed by the UAV. This trajectory is usually in two dimensions, and it assumes that GPS is available throughout the execution of the plan. The operator then decides whether the UAV should land or loiter at the end of the trajectory.
If GPS is jammed or not available, the current state-of-the-art—for small UAVs—is to teleoperate. Larger UAVs (like the Predator) are capable of maintaining localization for longer periods of time, due to the accurate, expensive, and heavy inertial navigation units they carry. On the small UAVs, this is not a choice. The MEMS-based inertial units (which fit the SWAP of the small vehicles) have enough inertial biases that they are not capable of flying without GPS, or at least not with sufficient accuracy. Therefore, teleoperation is the customary fall-back control methodology.
Teleoperation can be done two ways; one way is when the operator has direct line of sight (usually called remote control). This method is performed when the operator looks directly at the flying vehicle, and uses a joystick to control its position—as well as counteract the effects of wind and aerodynamics. A second mechanism, usually called FPV (First-Person View), is used when the operator controls, through an onboard camera, which is then relayed through a communication mechanism, such as a radio, satellite, or other communications channel, to the OCU (Operator Control Unit) carried by the operator.
For indoor applications, the choices are more limited. GPS is not available, and the UAVs capable of navigating in indoor scenarios cannot carry these larger, accurate IMUs. Therefore, the most common technique used for indoor missions is vehicle teleoperation. Teleoperation indoors is not trivial; the proximity of walls, and even the ground itself, create aerodynamic effects, which—in some cases—severely affect the controls of the UAV. Therefore, only trained operators can be used, and even under those conditions, safe control of the UAVs is not always accomplished.
Although autonomous mobility is the “Holy Grail” of autonomous robotic control in indoor and underground facilities, this is still to be accomplished. There are two main issues keeping autonomous mobility from being widespread. One, the sensors necessary for providing full, autonomous mobility, in an indoor facility, and are expensive and heavy. Two—and most importantly—the localization techniques for indoor navigation are hampered by the reduced SWAP. If a sufficient number of sensors is added to a quadrotor, capable of accurately mapping and localizing in an indoor facility, the cost and size of the UAV tends to make it unviable from a tactical standpoint.